Adaptive sensor fault-tolerant control for a class of multi-input multi-output nonlinear systems: Adaptive...

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Fault-Tolerant Control

Background:

• Multivariable nonlinear systems are susceptible to external disturbances, modeling errors, and time-varying sensor faults (bias, drift, loss of accuracy, loss of effectiveness).
• Existing fault-tolerant control (FTC) methods may face challenges with computational burden and control performance.

Purpose of the Study:

• To develop an adaptive fault-tolerant control (FTC) scheme for multivariable nonlinear systems.
• To effectively accommodate various sensor faults and external disturbances.
• To reduce computational burden and enhance control performance.

Main Methods:

• Integration of dynamic surface control (DSC) technique with adaptive first-order filters.
• Design of adaptation laws using novel low-pass filter based modification terms.
• Ensuring robust, fast, and high-accuracy estimation without high-frequency oscillations.

Main Results:

• The proposed adaptive FTC scheme effectively accommodates bias, drift, loss of accuracy, and loss of effectiveness faults.
• Demonstrated reduction in computational burden and improvement in control performance.
• Proof of uniform ultimate boundedness for all closed-loop system signals.

Conclusions:

• The developed adaptive FTC scheme is effective and superior for nonlinear systems with faults and disturbances.
• Tracking errors can be minimized to arbitrary levels.
• Simulation results validate the proposed method's performance.